mHealth Spectroscopy Measures Hemoglobin Optically
By HospiMedica International staff writers Posted on 08 Jun 2020 |
Image: Professor Kim using the Hemoglobin smartphone app (Photo courtesy of Vincent Walter/ Purdue University)
A novel smartphone-based technique helps assess blood hemoglobin (Hgb) and blood disorders without drawing blood, claims a new study.
Developed at Purdue University (Lafayette, IN, USA), Vanderbilt University (Nashville, TN, USA), and Moi University (Nairobi, Kenya), the smartphone app is based on spectral super-resolution (SSR) spectroscopy, which transforms the built-in camera of a smartphone into a hyperspectral imager, without the need for hardware modifications or accessories. The Hgb measurements are based on statistical learning of SSR of the eyelids, and reconstruction of the detailed spectra from the camera’s three color RGB data. To perform an Hgb measurement, the patient pulls down the inner eyelid to expose the small blood vessels underneath.
A healthcare professional then uses the smartphone app to take pictures of the inner eyelids. The SSR then extracts the detailed spectral information from the camera's images and a computational algorithm quantifies Hgb content from the data. The mobile app also includes features designed to stabilize image quality and synchronize the smartphone flashlight so as to obtain consistent images. The inner eyelid was selected as the sensing site because microvasculature is easily visible there, and it is not affected by skin color, which eliminates the need for any personal calibrations.
With the aid of a randomly selected group of 138 patients who had conventional blood tests at the Moi University Teaching and Referral Hospital, the researchers first trained the algorithm, and then tested the mobile health app with the remaining 15 volunteers. The results showed that the prediction errors for the smartphone technique were within 5-10% of those measured with clinical laboratory blood tests. They now plan to use the mobile health tool to assess nutritional status, anemia, and sickle cell disease. The study was published in the June 2020 issue of Optica.
“This new technology could be very useful for detecting anemia, which is characterized by low levels of blood hemoglobin. This is a major public health problem in developing countries, but can also be caused by cancer and cancer treatments,” said senior author Professor Young Kim, PhD, of Purdue University. "The COVID-19 pandemic has greatly increased awareness of the need for expanded mobile health and telemedicine services.”
Related Links:
Purdue University
Vanderbilt University
Moi University
Developed at Purdue University (Lafayette, IN, USA), Vanderbilt University (Nashville, TN, USA), and Moi University (Nairobi, Kenya), the smartphone app is based on spectral super-resolution (SSR) spectroscopy, which transforms the built-in camera of a smartphone into a hyperspectral imager, without the need for hardware modifications or accessories. The Hgb measurements are based on statistical learning of SSR of the eyelids, and reconstruction of the detailed spectra from the camera’s three color RGB data. To perform an Hgb measurement, the patient pulls down the inner eyelid to expose the small blood vessels underneath.
A healthcare professional then uses the smartphone app to take pictures of the inner eyelids. The SSR then extracts the detailed spectral information from the camera's images and a computational algorithm quantifies Hgb content from the data. The mobile app also includes features designed to stabilize image quality and synchronize the smartphone flashlight so as to obtain consistent images. The inner eyelid was selected as the sensing site because microvasculature is easily visible there, and it is not affected by skin color, which eliminates the need for any personal calibrations.
With the aid of a randomly selected group of 138 patients who had conventional blood tests at the Moi University Teaching and Referral Hospital, the researchers first trained the algorithm, and then tested the mobile health app with the remaining 15 volunteers. The results showed that the prediction errors for the smartphone technique were within 5-10% of those measured with clinical laboratory blood tests. They now plan to use the mobile health tool to assess nutritional status, anemia, and sickle cell disease. The study was published in the June 2020 issue of Optica.
“This new technology could be very useful for detecting anemia, which is characterized by low levels of blood hemoglobin. This is a major public health problem in developing countries, but can also be caused by cancer and cancer treatments,” said senior author Professor Young Kim, PhD, of Purdue University. "The COVID-19 pandemic has greatly increased awareness of the need for expanded mobile health and telemedicine services.”
Related Links:
Purdue University
Vanderbilt University
Moi University
Latest Health IT News
- Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients
- Strategic Collaboration to Develop and Integrate Generative AI into Healthcare
- AI-Enabled Operating Rooms Solution Helps Hospitals Maximize Utilization and Unlock Capacity
- AI Predicts Pancreatic Cancer Three Years before Diagnosis from Patients’ Medical Records
- First Fully Autonomous Generative AI Personalized Medical Authorizations System Reduces Care Delay
- Electronic Health Records May Be Key to Improving Patient Care, Study Finds
- AI Trained for Specific Vocal Biomarkers Could Accurately Predict Coronary Artery Disease
- First-Ever AI Test for Early Diagnosis of Alzheimer’s to Be Expanded to Diagnosis of Parkinson’s Disease
- New Self-Learning AI-Based Algorithm Reads Electrocardiograms to Spot Unseen Signs of Heart Failure
- Autonomous Robot Performs COVID-19 Nasal Swab Tests
- Statistical Tool Predicts COVID-19 Peaks Worldwide
- Wireless-Controlled Soft Neural Implant Stimulates Brain Cells
- Tiny Polymer Stent Could Treat Pediatric Urethral Strictures
- Human Torso Simulator Helps Design Brace Innovations
- 3D Bioprinting Rebuilds the Human Heart